YOlOV5技术在煤矿安全生产中的设计与实现

Design and Implementation of Yolov5 Technology in Coal Mine Safety Production

随着煤矿行业的发展,提高煤矿工作环境的安全性成为至关重要的任务,YOLOv5是一种高效的对象检测算法,具有快速的检测速度和出色的准确性。本研究通过构建适用于煤矿场景的数据集,训练YOLOv5模型,实现了在煤矿环境中的对象检测和隐患排查应用。实验结果表明,YOLOv5对象检测技术能够高效地检测煤矿场景中的人员、设备和其他潜在风险因素,提高了隐患监测和排查的速度、精度和实时响应能力,降低了事故风险,提高了工作效率,改善了煤矿运营的效率,降低了成本。

With the development of coal mining industry,improving the safety of coal mining working environment has become a crucial task.YOLOv5 is an efficient object detection algorithm with fast detection speed and excellent accuracy.By constructing data sets suitable for coal mine scenarios and training YOLOv5 model,this study realized the application of object detection and hidden danger detection in coal mine environment.The experimental results show that YOLOv5 object detection technology can efficiently detect personnel,equipment and other potential risk factors in the coal mine scene,improve the speed,accuracy and real-time response ability of hidden danger monitoring and investigation,reduce the accident risk,improve the work efficiency,improve the efficiency of coal mine operation,and reduce the cost.